遗传算法解决随机期望值模型问题的例题

Adaptive Resonance Theory Brain Modeling 人工智能人工神经网络源码-Adaptive Resonance Theory Brain Modeling artificial neural network artificial intelligence source

基本蚂蚁算法及其改进算法求解NP问题的论文汇总，而且全是中文，对于初学者一定有帮助-The basic ant algorithm and its improved algorithm for solving NP problems summary papers, and they are all Chinese, will certainly be helpful for beginners

文本分类算法很多，神经网络算法遗传算法可以用，本算法采用支持向量机SVM来实现-Text Classification Algorithm

是一个非常全面的pso的程序，有16个函数的测试，并且用三维图形将寻优过程显示出来。对所有的参数都可以修改测试-Is a very comprehensive procedure for the PSO, there are 16 function testing, and using three-dimensional graphics optimization process will be displayed. For all the parameters can modify the test

this demo is to show you how to implement a generic SIR (a.k.a. particle, bootstrap, Monte Carlo) filter to estimate the hidden states of a nonlinear, non-Gaussian state space model.-this demo is to show you how to implement a ge neric SIR (a.k.a. particle, the bootstrap. Monte Carlo) filter to estimate the hidden stat es of a nonlinear. non-Gaussian state space model.

加了动量项和域值，比较好用的bp网络算法-added value items and Victoria, better quality bp Network

改进遗传算法－郭涛算法做最优化问题很管用,算法的基本思想是 先任意产生n个随机数，然后从n个数里随机选择m个数，再有这m个 数合成一个新数，将这个新数同n个数中间适应值函数值的最差的比较， 如果好的话就取代最差的那个，如果它比最好的还要好的话，则把最好的 也取代。如果比最差的坏，则重新合成一个新数。依次循环下去。 程序的奇妙之处是GA_crossover()函数，产生的新数确实比较好，看看 那位大侠能改进一下，产生比这跟好的数。-improved genetic algorithm- Guo Tao done optimization algorithm is very effective, and the algorithm is the first basic idea arbitrary n generated random number and then the number li n m randomly selected number, and this number m of a new synthesis of the new middle with n number fitness function of the worst by comparison, if a good case to replace the worst, um, if it even than the best, then ruled the best have replaced. If worse than the worst, a de novo synthesis of new. Followed by the cycle continues. The magic of procedures is GA_crossover () function, the new really good to see heroes who can be improved upon, it generated more than a few with a good.

RBFMIP is a package for training multi-instance RBF neural networks

该文档是清华大学的模式识别教程，该版本是网页版本，浏览非常方便，内容也非常详细，非常适合初学者，个人举得特别是支持向量机那一章描述很棒！-this document is from Tsinghua University,this is the html version,it is convenient to read, it is very suitable for the elementary readers,in my own opinion,the charter of svm is very detail and easily understandable.

本算法采用最基本的遗传算法编写，有利于初学者掌握遗传算法的构成。-This algorithm is written by the most fundamental genetic algorithm,benefit the beginner to know the structure of genetic algorithm